PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF (MFEM)
Seasonality Analysis
PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF Annual Seasonality Statistics
PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF Monthly Seasonality Performance
| Month | Avg Return | Win Rate | Strength |
|---|---|---|---|
| January | 1.88% | Moderate | |
| February | -1.34% | Very Weak | |
| March WORST | -3.16% | Weak | |
| April | 2.15% | Strong | |
| May | 1.52% | Strong | |
| June | 0.19% | Moderate | |
| July | 1.49% | Moderate | |
| August | -0.03% | Weak | |
| September | -0.66% | Weak | |
| October | -1.08% | Weak | |
| November BEST | 2.17% | Weak | |
| December | -1.03% | Weak |
PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF 2026 vs Historical Pattern
PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF Interactive Seasonality Chart
PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF Pattern Scanner
PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF Seasonal Historical Performance
About PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF (MFEM) Seasonality
PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF (MFEM) has been analyzed using 9 years of historical data to identify seasonal patterns. Classified under ETFs, PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF shows distinct seasonal tendencies based on historical data.
The strongest month for PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF is historically November, with an average return of 2.17% and a win rate of 44%. Conversely, March tends to be the weakest month, averaging -3.16% return.
Looking at the full calendar year, PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF has an average annual return of 2.10% with an overall monthly win rate of 51.3%. Out of 12 months, 6 typically show positive average returns.
The seasonal pattern for PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF has a consistency score of 49.1 (Poor), based on 10 years of data. Higher consistency means the seasonal pattern has been more reliable across different market conditions.
PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF Seasonality FAQ
What is the best month to buy PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF (MFEM)?
Historically, November has been the best month for PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF, with an average return of 2.17% and a win rate of 44%. However, past performance does not guarantee future results.
What is the worst month for PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF (MFEM)?
Based on historical data, March has been the weakest month for PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF, with an average return of -3.16%. This is a historical observation and does not guarantee future results.
How reliable is MFEM seasonality data?
The seasonality analysis for PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF is based on 9 years of historical price data. While seasonal patterns can provide useful insights, they should be combined with other forms of analysis. Past patterns do not guarantee future performance.
How can I use PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF seasonality in my trading?
Use PIMCO Equitiy Series PIMCO RAFI Dynamic Multi-Factor Emerging Markets Equity ETF (MFEM) seasonality as one factor in your analysis. Identify historically strong and weak months, combine with other research methods. SeasOptima provides premium tools including interactive charts, pattern scanning, and historical performance data for deeper analysis.